Invariance of Weight Distributions in Rectified MLPs. - Russell Tsuchida; Farbod Roosta-Khorasani; Marcus Gallagher (ICML, 2018)

Exchangeability and Kernel Invariance in Trained MLPs. - Russell Tsuchida; Fred (Farbod) Roosta; Marcus Gallagher (IJCAI, 2019)

Expressive Priors in Bayesian Neural Networks: Kernel Combinations and Periodic Functions. - Tim Pearce; Russell Tsuchida; Mohamed Zaki; Alexandra Brintrup; Andy Neely (UAI, 2019)

Richer priors for infinitely wide multi-layer perceptrons. - Russell Tsuchida; Fred Roosta; Marcus Gallagher (CoRR, 2019)

Results on infinitely wide multi-layer perceptrons - Russell Tsuchida (2020)

Avoiding Kernel Fixed Points: Computing with ELU and GELU Infinite Networks. - Russell Tsuchida; Tim Pearce; Christopher van der Heide; Fred Roosta; Marcus Gallagher (AAAI, 2021)

Gaussian Process Bandits with Aggregated Feedback. - Mengyan Zhang 001; Russell Tsuchida; Cheng Soon Ong (AAAI, 2022)

Declarative nets that are equilibrium models. - Russell Tsuchida; Suk Yee Yong; Mohammad Ali Armin; Lars Petersson; Cheng Soon Ong (ICLR, 2022)

Efficient Gaussian Process Model on Class-Imbalanced Datasets for Generalized Zero-Shot Learning. - Changkun Ye; Nick Barnes; Lars Petersson; Russell Tsuchida (ICPR, 2022)

Deep equilibrium models as estimators for continuous latent variables. - Russell Tsuchida; Cheng Soon Ong (AISTATS, 2023)

Squared Neural Families: A New Class of Tractable Density Models. - Russell Tsuchida; Cheng Soon Ong; Dino Sejdinovic (NeurIPS, 2023)

Earth Movers in The Big Data Era: A Review of Optimal Transport in Machine Learning. - Abdelwahed Khamis; Russell Tsuchida; Mohamed Tarek; Vivien Rolland; Lars Petersson (CoRR, 2023)

Stochastic gradient updates yield deep equilibrium kernels. - Russell Tsuchida; Cheng Soon Ong (Trans. Mach. Learn. Res., 2023)

Exact, Fast and Expressive Poisson Point Processes via Squared Neural Families. - Russell Tsuchida; Cheng Soon Ong; Dino Sejdinovic (AAAI, 2024)

Label Shift Estimation for Class-Imbalance Problem: A Bayesian Approach. - Changkun Ye; Russell Tsuchida; Lars Petersson; Nick Barnes (WACV, 2024)

Gaussian Ensemble Belief Propagation for Efficient Inference in High-Dimensional Systems. - Daniel MacKinlay; Russell Tsuchida; Daniel Edward Pagendam; Petra Kuhnert (CoRR, 2024)

Open Set Label Shift with Test Time Out-of-Distribution Reference. - Changkun Ye; Russell Tsuchida; Lars Petersson; Nick Barnes (CVPR, 2025)

Gaussian Ensemble Belief Propagation for Efficient Inference in High-Dimensional, Black-box Systems. - Daniel MacKinlay; Russell Tsuchida; Daniel Edward Pagendam; Petra Kuhnert (ICLR, 2025)

Label Distribution Learning using the Squared Neural Family on the Probability Simplex. - Daokun Zhang; Russell Tsuchida; Dino Sejdinovic (UAI, 2025)

Generalization Certificates for Adversarially Robust Bayesian Linear Regression. - Mahalakshmi Sabanayagam; Russell Tsuchida; Cheng Soon Ong; Debarghya Ghoshdastidar (CoRR, 2025)

Squared families: Searching beyond regular probability models. - Russell Tsuchida; Jiawei Liu; Cheng Soon Ong; Dino Sejdinovic (CoRR, 2025)